Enosis Outsourcing logo
EndorsedendorsedCompleted

Private Cloud Data Engineering & ML Configuration for Consultancy

Services Covered:

Cloud Consulting and Services • Data Engineering • AI and Machine Learning
Project hero — replace with case study imagery
Industry
Industry

Healthcare

Duration
Duration

17 months

Budget
Budget

50K - 199K

Start Date
Start Date

1 June 2019

Team Size
Team Size

1-5

Engagement Model
Engagement Model

Onshore

Project Capability Score (PCS)

gauge meter
76/100
Good

Project Capability Score (PCS) estimates how capable DS Stream is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

Confidential

mapWarsaw, Poland

Project Summary

DS Stream provided configuration and environment setup in cloud data and delivered a data engineering solution that enabled machine-learning analysis and models to predict customer behavior. The vendor used a tech stack including AWS, Triton, Oracle, Airflow, Hive, Docker, S3, EC2 and Scala. The end deliverables met all client requirements; the client noted DS Stream was responsive and quick to requests and that further phases are planned.

Key Challenges

  • Enable better resource planning and higher profits through AI/ML algorithms
  • Provide configuration and environment setup in a private cloud for CRM and medical data

Project Deliverables

  • Configuration and environment setup in private cloud
  • Data engineering pipelines for CRM and medical data
  • Machine learning models to predict customer behavior

Project Solution

DS Stream delivered a Data Engineering project deployed in a private cloud to enable machine-learning analysis. The vendor built data pipelines ingesting CRM and medical sources, configured the environment (using AWS, S3, EC2, Docker) and used tools including Triton, Oracle, Airflow, Hive, Hue, Sqoop and Scala. A small team of engineers (about four people on contract) implemented the configuration and produced models to predict customer behavior.

Project Outcome

  • The project fulfilled all client's requirements and received positive feedback.
  • The vendor was responsive and quick to requests, enabling effective collaboration.
  • New phases were planned to further extend the solution's functionalities.

Platforms

  • CloudCloud

Tech Stack

  • Amazon Web Services (AWS)Amazon Web Services (AWS)
  • Amazon EC2Amazon EC2
  • OracleOracle
  • ScalaScala
  • S3S3
  • Apache AirflowApache Airflow
  • Apache HiveApache Hive
  • DockerDocker

Client Endorsement

Overall Review Rating

5star

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“The end deliverables completed all client's requirements and received positive feedback. DS Stream was responsive and quick to all the requests given.”

Maciej Moscicki

CEO

Note: This endorsement is based on publicly available client feedback from external review sources.